{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 什么是统计套利？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 目录\n",
    "1. 什么是统计套利？\n",
    "2. 统计套利有哪些策略？\n",
    "3. 什么是价差与正反向套利？\n",
    "4. 如何执行价差套利策略？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 什么是统计套利？\n",
    "统计套利是根据价差同时买入与卖出一样或极为相似的品种。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 统计套利有哪些策略？\n",
    "- 跨市场套利： 不同市场的相同或相似资产\n",
    "- 期现套利： 期货与现货市场\n",
    "- 跨期套利： 同一品种不同月份期限的合约\n",
    "- 跨品种套利： 品种不同但高度相关\n",
    "- 期权套利： 蝶式鹰式"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 什么是价差与正反向套利？\n",
    "统计套利中的价差指的是两相似品种的价格差。\n",
    "\n",
    "正向套利： 买入近期，卖出远期； 买大豆，卖豆油。\n",
    "\n",
    "反向套利： 卖出近期，买入远期； 卖大豆，买豆油。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          000001    002142    002807    600000    600015    600016    600036  \\\n",
      "601398  0.646295  0.633016 -0.003869  0.660767  0.702180  0.675402  0.708044   \n",
      "601288  0.712308  0.687464  0.056656  0.712871  0.749461  0.715849  0.724441   \n",
      "601939  0.710729  0.695258  0.065037  0.710462  0.750733  0.711134  0.737558   \n",
      "601988  0.649307  0.667511 -0.014668  0.668540  0.712895  0.675092  0.687078   \n",
      "601328  0.761541  0.769728 -0.059440  0.791300  0.808284  0.760073  0.776672   \n",
      "\n",
      "          600908    600919    600926    ...       601229    601288    601328  \\\n",
      "601398  0.070917  0.268633  0.166524    ...     0.109151  0.846453  0.768690   \n",
      "601288  0.182855  0.394113  0.343021    ...     0.318859  1.000000  0.810580   \n",
      "601939  0.093011  0.369322  0.262706    ...     0.201923  0.859619  0.815114   \n",
      "601988  0.176225  0.387991  0.264471    ...     0.209826  0.858944  0.798573   \n",
      "601328  0.113708  0.352060  0.245626    ...     0.194302  0.810580  1.000000   \n",
      "\n",
      "          601398    601818    601939    601988    601997    601998    603323  \n",
      "601398  1.000000  0.725766  0.829206  0.819348  0.285246  0.644814 -0.044188  \n",
      "601288  0.846453  0.787926  0.859619  0.858944  0.335723  0.688575  0.151845  \n",
      "601939  0.829206  0.779576  1.000000  0.827845  0.333016  0.697057 -0.001182  \n",
      "601988  0.819348  0.787112  0.827845  1.000000  0.425697  0.714082  0.079610  \n",
      "601328  0.768690  0.837103  0.815114  0.798573  0.289925  0.748342  0.039695  \n",
      "\n",
      "[5 rows x 24 columns]\n"
     ]
    }
   ],
   "source": [
    "#寻找银行类股票的套利机会\n",
    "import pandas as pd\n",
    "import tushare as ts\n",
    "\n",
    "codes = ['000001', '002142', '002807', '600000', '600015', \n",
    "         '600016', '600036', '600908', '600919', '600926',\n",
    "         '601009', '601128', '601166', '601169', '601229',\n",
    "        '601288', '601328', '601398', '601818', '601939',\n",
    "        '601988', '601997', '601998', '603323']\n",
    "\n",
    "stocks_dict = {}\n",
    "for c in codes:\n",
    "    stock = ts.get_k_data(c, start='2010-01-01', ktype='D', autype='qfq')\n",
    "    stock.index = pd.to_datetime(stock['date'], format='%Y-%m-%d')\n",
    "    stock.pop('date')\n",
    "    stocks_dict[c] = stock\n",
    "\n",
    "pn = pd.Panel(stocks_dict)\n",
    "\n",
    "returns = pn.minor_xs('close').pct_change()[1:]\n",
    "corr_r = returns.corr()\n",
    "print corr_r.nlargest(5, columns='601398')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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kT7vY5HL8ERARkUNzuS2i8pIKsQVk3KJBNDtuz9US4R79W4lF/Jvk3OxD8DYQxt+uCbdQ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\nYjAYDIZJYQMRg8FgMEzK/wE1RiGn6EsIsgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1165f7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sns.heatmap(corr_r, square=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.10942409639\n"
     ]
    },
    {
     "data": {
      "image/png": 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QK86ZWC3LHwji//61G0dOt0ffOQ6kE47DbpVF7so0YckDuWlXfUT948GhoBJp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a3c320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#选择601398，601288\n",
    "import numpy as np\n",
    "\n",
    "close = pn.minor_xs('close')\n",
    "data = pd.concat([close['601398'], close['601288']], axis=1)\n",
    "data['P_diff'] = data.iloc[:,0]-data.iloc[:,1]\n",
    "# print data.P_diff\n",
    "diff_mean = data.P_diff[:-400].mean()\n",
    "print diff_mean\n",
    "diff_std = data.P_diff[:-400].std()\n",
    "\n",
    "plt.plot(data.P_diff)\n",
    "plt.hlines(diff_mean, data.index[0], data.index[-400])\n",
    "plt.hlines(diff_mean+2*diff_std, data.index[0], data.index[-400], colors='r')\n",
    "plt.hlines(diff_mean-2*diff_std, data.index[0], data.index[-400], colors='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 如何执行价差套利策略？\n",
    "1. 价差区间超买超卖交易（买弱卖强）\n",
    "    - 在上安全边际买入弱的卖出强的\n",
    "2. 反向交易（买强卖弱）\n",
    "    - 在上穿均值后买入强的卖出弱的\n",
    "3. 在更强的位置重复加仓\n",
    "    - 在穿越安全边际后继续做空价差"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
